Learn Data Science and Machine Learning on Microsoft Azure

Create and customize bar charts from Excel grocery price data to visualize price variation over time with stacked bars, time frames, and color formatting.

Create a line chart in Power BI by placing date on the axis, price on values, and product on the legend, then adjust data labels and line style.

Learn to create and customize Power BI pie chart from a billing dataset, using product category as the category and order quantity as the measure, with label and color formatting.

Learn to create a ring chart and link it with a pie chart using category and subcategory data, format data labels with percentages, coordinate colors, and design a synchronized dashboard.

Learn to build an interactive treemap in Power API, linked with pie and ring charts to reveal country- and category-level insights and customize formatting and colors for cross-chart interactivity.

Learn how drill down connects tables, matrices, and charts to reveal deeper data by selecting a row, column, country, or category and seeing real-time updates.

Create and use a slicer to filter visualizations by country and state with multi-select checkboxes, linking the slicer to charts for focused analysis across US and Canada.

Create and use a date slicer to filter visuals by start and end dates, with a date hierarchy and slider, enabling real-time, script-free data exploration.

Create a measure (calculated field) in Power BI to build gauge charts with a target line, using profit calculations and multiple chart types.

Learn to build a simple map in power with multiple map modes, using countries, states, and regions, adjust bubble sizes by order quantity, customize colors, tooltips, and map styles.

Explore an advanced scatterplot with animation playback, showing x axis as the average order quantity and y axis as the sum, with bubble size representing profit over time.

Learn Power Query in Excel or Power BI by transforming data, deleting top or bottom rows, splitting columns with a delimiter, applying and undoing steps, and loading results into dashboards.

Master the Power Query replace values feature in Power BI to clean data by replacing column values, like United States of America with USA, and optimizing large spreadsheets.

Learn how to install Python and essential data science packages in Power BI, configure the Python environment, install pandas with pip, and create Python visualizations in Power BI.

Learn to create a simple line chart in Power BI using Python and matplotlib by importing Excel data, selecting x and y axes, and customizing the chart's formatting.

Learn to enhance data visuals by adding x and y axis labels, creating and customizing dashed line and scatter plots, and combining chart types in Python and Power BI.

Create a computer vision service to analyze images, extract domain-specific details, recognize landmarks and people, extract text, and generate thumbnails using Python scripts and API keys.

Create and deploy a computer vision connected service on Azure, generate image descriptions and text in images, recognize celebrities and landmarks, and run operations with Python and the SDK.

Create and deploy a text analytics service on Microsoft Azure, configure service name, subscription, and location, then access keys and quick start resources.

Explore how to use text analytics on Microsoft Azure to detect language, perform sentiment analysis, extract features, and apply name entity depletion, with hands-on setup and sample scripts.

Explore text analytics on Microsoft Azure, focusing on language detection and sentiment analysis through API scripts and sample outputs.

Explore text analytics to extract key phrases from sentences, compare sentiment analysis, and detect user intent to drive appropriate responses.

Demonstrate text analytics and entity recognition by identifying linked entities, such as Microsoft as an organization and technology company, and linking results to Wikipedia pages.